Increased parasite load is associated with reduced metabolic rates and escape responsiveness in pumpkinseed sunfish
Bibliographic record
Abstract
Wild animals have parasites that can compromise their physiological and/or behavioural performance. Yet, the extent to which parasite load is related to intraspecific variation in performance traits within wild populations remains relatively unexplored. We used pumpkinseed sunfish (Lepomis gibbosus) and their endoparasites as a model system to explore the effects of infection load on host aerobic metabolism and escape performance. Metabolic traits (standard and maximum metabolic rates, aerobic scope) and fast-start escape responses following a simulated aerial attack by a predator (responsiveness, response latency and escape distance) were measured in fish from across a gradient of visible (i.e. trematodes causing black spot disease counted on fish surfaces) and non-visible (i.e. cestodes in fish abdominal cavity counted post-mortem) endoparasite infection. We found that a higher infection load of non-visible endoparasites was related to lower standard and maximum metabolic rates, but not aerobic scope in fish. Non-visible endoparasite infection load was also related to decreased responsiveness of the host to a simulated aerial attack. Visible endoparasites were not related to changes in metabolic traits or fast-start escape responses. Our results suggest that infection with parasites that are inconspicuous to researchers can result in intraspecific variation in physiological and behavioural performance in wild populations, highlighting the need to more explicitly acknowledge and account for the role played by natural infections in studies of wild animal performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".